Social media analytics and business intelligence research: A systematic review

被引:69
作者
Choi, Jaewoong [1 ]
Yoon, Janghyeok [1 ]
Chung, Jaemin [1 ]
Coh, Byoung-Youl [2 ]
Lee, Jae-Min [2 ]
机构
[1] Konkuk Univ, Dept Ind Engn, 120 Neungdong Ro, Seoul 05029, South Korea
[2] Korea Inst Sci & Technol Informat, Future Technol Anal Ctr, 66 Hoegiro, Seoul 02456, South Korea
基金
新加坡国家研究基金会;
关键词
Social media; Online VoC; Open data; Business intelligence; Systematic review; Sentiment analysis; TECHNOLOGY OPPORTUNITY DISCOVERY; ONLINE PRODUCT REVIEWS; SENTIMENT ANALYSIS; BIG DATA; CONSUMER PERCEPTIONS; VALUE CREATION; PREDICTION; NETWORK; CLASSIFICATION; MANAGEMENT;
D O I
10.1016/j.ipm.2020.102279
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Evidently, online voice of customers (VoC) expressed in social media has emerged as quality data for researchers who are willing to conduct customer-driven business intelligence (BI) research. Nevertheless, to the best of authors' knowledge, there is still a dearth of studies that deal with such remarkable research stream and address various open data (e.g., social media, intellectual property) from a BI research perspective. Therefore, this study has attempted to evaluate the applicability of social media data in BI research and provide a systematic review on the primary research articles in the domain. This study compared social media data with the other open data (e.g., gray literature, public government data) in terms of data content, collection, updatability and structure, which are determined through a thorough discussion with experts. Next, this study selected 57 social media-based BI research articles from the Web of Science (WoS) database and analyzed them with three research questions about the data, methodologies, and results to understand this research domain. Our findings are expected to inform the existing researchers in the research domain about the future research directions, enable newcomers to understand the overall process of analyzing social media data, and provide the practitioners with social media analysis approaches suitable for their environment.
引用
收藏
页数:18
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